3. MEASUREMENT ERRORS AND THE MEASUREMENT PROCESS

Measurements of any kind, in any experiment, are always subject to
uncertainties or errors, as they are more often called. We will argue
in this section that the measurement process is, in fact, a random
process described by an abstract probability distribution whose
parameters contain the information desired. The results of a
measurement are then samples from this distribution which allow an
estimate of the theoretical parameters. In this view, measurement
errors can be seen then as sampling errors.

Before going into this argument, however, it is first necessary to
distinguish between two types of errors: systematic and random.